Software Engineer, Enterprise
Software Engineer, Enterprise

Software Engineer, Enterprise

Full-Time 60000 - 80000 ÂŁ / year (est.) Home office (partial)
Scale AI

At a Glance

  • Tasks: Design and build scalable backend systems for enterprise AI products.
  • Company: Join Scale AI, a leader in the Generative AI revolution.
  • Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
  • Why this job: Be at the forefront of AI innovation and make a real impact.
  • Qualifications: 4+ years in backend development with strong skills in Python or TypeScript.
  • Other info: Collaborative environment with a focus on cutting-edge technology.

The predicted salary is between 60000 - 80000 ÂŁ per year.

At Scale AI, we’re not just building AI tools—we’re pioneering the next era of enterprise AI. As businesses race to harness the power of Generative AI, Scale is at the forefront, delivering cutting‑edge solutions that transform workflows, automate complex processes, and drive unparalleled efficiency for the largest enterprises. Our Scale Generative AI Platform (SGP) provides foundational services and APIs, enabling businesses to seamlessly integrate AI into their operations at production scale.

We’re looking for a Backend Engineer to help bring large‑scale GenAI systems to production. In this role, you’ll build the core infrastructure that powers AI products for some of the world’s largest enterprises—designing scalable APIs, distributed data systems, and robust deployment pipelines that enable production‑grade reliability and performance. This is a rare opportunity to be at the center of the GenAI revolution, solving hard backend and infrastructure challenges that make AI truly work at enterprise scale. If you're excited about shaping how AI systems are deployed and scaled in the real world, we want to hear from you.

You Will:

  • Design, build, and scale backend systems that power enterprise GenAI products, focusing on reliability, performance, and deployment across both Scale’s and customers’ infrastructure.
  • Develop core services and APIs that integrate AI models and enterprise data sources securely and efficiently, enabling production‑scale AI adoption.
  • Architect scalable distributed systems for data processing, inference, and orchestration of large‑scale GenAI workloads.
  • Optimize backend performance for latency, throughput, and cost—ensuring AI applications can operate at enterprise scale across hybrid and multi‑cloud environments.
  • Manage and evolve cloud infrastructure (AWS, Azure, or GCP), driving automation, observability, and security for large‑scale AI deployments.
  • Collaborate with ML and product teams to bring cutting‑edge GenAI models into production through efficient APIs, model serving systems, and evaluation frameworks.
  • Continuously improve reliability and scalability, applying strong engineering practices to make AI systems robust, maintainable, and enterprise‑ready.

Ideally, You Have:

  • 4+ years of experience developing large‑scale backend or infrastructure systems, with a strong emphasis on distributed services, reliability, and scalability.
  • Proficiency in Python or TypeScript, with experience designing high‑performance APIs and backend architectures using frameworks such as FastAPI, Flask, Express, or NestJS.
  • Deep familiarity with cloud infrastructure (AWS and Azure preferred), including container orchestration (Kubernetes, Docker) and Infrastructure‑as‑Code tools like Terraform.
  • Experience managing data systems such as relational and NoSQL databases (PostgreSQL, DynamoDB, etc.) and building pipelines for data‑intensive applications.
  • Hands‑on experience with GenAI applications, model integration, or AI agent systems—understanding how to deploy, evaluate, and scale AI workloads in production.
  • Strong understanding of observability, CI/CD, and security best practices for running services in enterprise or multi‑tenant environments.
  • Ability to balance rapid iteration with production‑grade quality, shipping reliable backend systems in fast‑paced environments.
  • Collaborative mindset, working closely with ML, infra, and product teams to bring complex GenAI systems into production at enterprise scale.

About Us:

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high‑quality data and full‑stack technologies that power the world’s leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace.

Software Engineer, Enterprise employer: Scale AI

At Scale AI, we pride ourselves on being at the forefront of the Generative AI revolution, offering our employees a dynamic work culture that fosters innovation and collaboration. With a strong commitment to professional growth, we provide ample opportunities for skill development and career advancement, all while working on cutting-edge technology that has a real impact on enterprise operations. Our inclusive environment ensures that every team member can bring their whole self to work, making Scale an exceptional place to build a meaningful career in AI.
Scale AI

Contact Detail:

Scale AI Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Software Engineer, Enterprise

✨Tip Number 1

Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.

✨Tip Number 2

Show off your skills! Create a portfolio or GitHub repository showcasing your projects, especially those related to backend systems and APIs. This gives potential employers a taste of what you can do and sets you apart from the crowd.

✨Tip Number 3

Prepare for interviews by practising common technical questions and coding challenges. Use platforms like LeetCode or HackerRank to sharpen your skills. Remember, confidence is key—show them you know your stuff!

✨Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are genuinely interested in joining our mission at Scale AI.

We think you need these skills to ace Software Engineer, Enterprise

Backend Development
API Design
Distributed Systems
Cloud Infrastructure Management
Python
TypeScript
FastAPI
Flask
Express
NestJS
Kubernetes
Docker
Terraform
Relational Databases
NoSQL Databases
CI/CD

Some tips for your application 🫡

Tailor Your Application: Make sure to customise your CV and cover letter for the Software Engineer role. Highlight your experience with backend systems, APIs, and cloud infrastructure, as these are key to what we’re looking for at Scale AI.

Showcase Your Skills: Don’t just list your skills—demonstrate them! Include specific examples of projects where you’ve designed scalable systems or optimised performance. We love seeing how you’ve tackled challenges in your previous roles.

Be Clear and Concise: Keep your application clear and to the point. Use bullet points for easy reading and make sure to highlight your most relevant experiences. We appreciate straightforward communication!

Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy!

How to prepare for a job interview at Scale AI

✨Know Your Tech Stack

Make sure you’re well-versed in the technologies mentioned in the job description, especially Python or TypeScript. Brush up on frameworks like FastAPI or Flask, and be ready to discuss how you've used them in past projects.

✨Showcase Your Problem-Solving Skills

Prepare to discuss specific challenges you've faced in backend development, particularly around scalability and reliability. Use examples that highlight your ability to design robust systems and how you approached complex problems.

✨Understand Cloud Infrastructure

Familiarise yourself with cloud platforms like AWS or Azure, and be prepared to talk about your experience with container orchestration tools like Kubernetes. Highlight any projects where you’ve managed cloud infrastructure for large-scale applications.

✨Collaborate and Communicate

Since collaboration is key in this role, think of examples where you worked closely with ML or product teams. Be ready to discuss how you ensure smooth communication and integration between different teams to bring AI systems into production.

Software Engineer, Enterprise
Scale AI

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